May 18, 2019 — Stephen Wolfram
The Wolfram|Alpha Story
Today it’s 10 years since we launched Wolfram|Alpha. At some level, Wolfram|Alpha is a never-ending project. But it’s had a great first 10 years. It was a unique and surprising achievement when it first arrived, and over its first decade it’s become ever stronger and more unique. It’s found its way into more and more of the fabric of the computational world, both realizing some of the long-term aspirations of artificial intelligence, and defining new directions for what one can expect to be possible. Oh, and by now, a significant fraction of a billion people have used it. And we’ve been able to keep it private and independent, and its main website has stayed free and without external advertising.
Get Full Access to the Wolfram Language from Python
The Wolfram Language gives programmers a unique computational language with an enormous array of sophisticated algorithms and built-in real-world knowledge. For many years, people have asked us how to access all the power of our technology from other software environments and programming languages. And over the years, we have built many such connections, like Wolfram CloudConnector for Excel, WSTP (Wolfram Symbolic Transfer Protocol) for C/C++ programs and, of course, J/Link, which provides access to the Wolfram Language directly from Java.
So today we’re happy to formally announce a new and often-requested connection that allows you to call the Wolfram Language directly and efficiently from Python: the Wolfram Client Library for Python. And, even better, this client library is fully open source as the WolframClientForPython git repository under the MIT License, so you can clone it and use it any way you see fit.
May 9, 2019 — Stephen Wolfram
What Kind of a Thing Is the Wolfram Language?
I’ve sometimes found it a bit of a struggle to explain what the Wolfram Language really is. Yes, it’s a computer language—a programming language. And it does—in a uniquely productive way, I might add—what standard programming languages do. But that’s only a very small part of the story. And what I’ve finally come to realize is that one should actually think of the Wolfram Language as an entirely different—and new—kind of thing: what one can call a computational language.
So what is a computational language? It’s a language for expressing things in a computational way—and for capturing computational ways of thinking about things. It’s not just a language for telling computers what to do. It’s a language that both computers and humans can use to represent computational ways of thinking about things. It’s a language that puts into concrete form a computational view of everything. It’s a language that lets one use the computational paradigm as a framework for formulating and organizing one’s thoughts.
It’s only recently that I’ve begun to properly internalize just how broad the implications of having a computational language really are—even though, ironically, I’ve spent much of my life engaged precisely in the consuming task of building the world’s only large-scale computational language.
May 2, 2019 — Tuseeta Banerjee, Research Scientist, Machine Learning
If you haven’t used machine learning, deep learning and neural networks yourself, you’ve almost certainly heard of them. You may be familiar with their commercial use in self-driving cars, image recognition, automatic text completion, text translation and other complex data analysis, but you can also train your own neural nets to accomplish tasks like identifying objects in images, generating sequences of text or segmenting pixels of an image. With the Wolfram Language, you can get started with machine learning and neural nets faster than you think. Since deep learning and neural networks are everywhere, let’s go ahead and explore what exactly they are and how you can start using them.
April 26, 2019 — Tim Shedelbower, Visualization Developer, Algorithms R&D
Connect the dots. It was exciting to draw from number to number until the sudden discovery of a hidden cartoon. That was my inadvertent introduction to graph theory very early in school. Little did I know adults used the same concept to discover hidden patterns to solve problems, such as proving that a single crossing of seven Königsberg bridges to four land masses is not possible, but coloring a map distinctly with four colors is. These problems inspired the methods we know today as graph theory. And in honor of the work of late mathematician and connect-the-dot author Elwyn Berlekamp, we see how sophisticated this “child’s play” can be by examining the different styles and themes we can apply to graphs.
April 16, 2019 — Stephen Wolfram
Today we’re releasing Version 12 of Wolfram Language (and Mathematica) on desktop platforms, and in the Wolfram Cloud. We released Version 11.0 in August 2016, 11.1 in March 2017, 11.2 in September 2017 and 11.3 in March 2018. It’s a big jump from Version 11.3 to Version 12.0. Altogether there are 278 completely new functions, in perhaps 103 areas, together with thousands of different updates across the system:
April 11, 2019 — Swede White, Public Relations Manager
Every year, the U.S. Department of State sponsors a worldwide competition called Fishackathon. Its goal is to protect life in our waters by creating technological solutions to help solve problems related to fishing.
The first global competition was held in 2014 and has been growing massively every year. In 2018 the winning entry came from a five-person team from Boston, after competing against 45,000 people in 65 other cities spread across 5 continents. The participants comprised programmers, web and graphic designers, oceanographers and biologists, mathematicians, engineers and students who all worked tirelessly over the course of two days.
To find out more about the winning entry for Fishackathon in 2018 and how the Wolfram Language has helped make the seas safer, we sat down with Michael Sollami to learn more about him and his team’s solution to that year’s challenge.
April 9, 2019 — Alec Titterton, CBM Content Development Manager, European Sales
Wolfram Research is pleased to announce further collaboration with the Raspberry Pi Foundation as part of supporting makers across the world through education. A collection of 10 Wolfram Language projects has been launched on the foundation’s projects site. These projects range from creating weather dashboards to building machine learning classifiers to using AI for facial recognition. The goal is to put the power of computational intelligence into the hands of anyone who wants access—democratizing the skills that will increasingly be needed to innovate and discover what is possible with modern computation.
By providing easy-to-follow, step-by-step tutorials that result in a finished, functioning piece of software, Wolfram aims to lower the barrier of entry for those who wish to get immediately started programming, building and making. Projects can be completely built on the Raspberry Pi or within a web browser in the Wolfram Cloud.
Drawing on Autopilot: Automated Plane (Geometry) Illustrations from The American Mathematical Monthly
April 4, 2019 — Dan McDonald, Lead Developer, Synthetic Geometry Project
Version 12 of the Wolfram Language introduces the functions GeometricScene, RandomInstance and FindGeometricConjectures for representing, drawing and reasoning about problems in plane geometry. In particular, abstract scene descriptions can be automatically supplied with coordinate values to produce diagrams satisfying the conditions of the scene. Let’s apply this functionality to some of the articles and problems about geometry appearing in the issues of The American Mathematical Monthly from February and March of 2019.
April 2, 2019 — Jon McLoone, Director, Technical Communication & Strategy
Over the years, I have been asked many times about my opinions on free and open-source software. Sometimes the questions are driven by comparison to some promising or newly fashionable open-source project, sometimes by comparison to a stagnating open-source project and sometimes by the belief that Wolfram technology would be better if it were open source.
At the risk of provoking the fundamentalist end of the open-source community, I thought I would share some of my views in this blog. While there are counterexamples to most of what I have to say, not every point applies to every project, and I am somewhat glossing over the different kinds of “free” and “open,” I hope I have crystallized some key points.